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  1. Increased wildfire events constitute a significant threat to life and property in the United States. Wildfire impact on severe storms and weather hazards is another pathway that threatens society, and our understanding of which is very limited. Here, we use unique modeling developments to explore the effects of wildfires in the western US (mainly California and Oregon) on precipitation and hail in the central US. We find that the western US wildfires notably increase the occurrences of heavy precipitation rates by 38% and significant severe hail (≥2 in.) by 34% in the central United States. Both heat and aerosols from wildfires play an important role. By enhancing surface high pressure and increasing westerly and southwesterly winds, wildfires in the western United States produce ( 1 ) stronger moisture and aerosol transport to the central United States and ( 2 ) larger wind shear and storm-relative helicity in the central United States. Both the meteorological environment more conducive to severe convective storms and increased aerosols contribute to the enhancements of heavy precipitation rates and large hail. Moreover, the local wildfires in the central US also enhance the severity of storms, but their impact is notably smaller than the impact of remotemore »wildfires in California and Oregon because of the lessened severity of the local wildfires. As wildfires are projected to be more frequent and severe in a warmer climate, the influence of wildfires on severe weather in downwind regions may become increasingly important.« less
    Free, publicly-accessible full text available November 1, 2023
  2. Abstract. A new technique was used to directly measure O3 response to changes inprecursor NOx and volatile organic compound (VOC) concentrations in the atmosphere using threeidentical Teflon smog chambers equipped with UV lights. One chamberserved as the baseline measurement for O3 formation, one chamber addedNOx, and one chamber added surrogate VOCs (ethylene, m-xylene,n-hexane). Comparing the O3 formation between chambers over a3-hour UV cycle provides a direct measurement of O3 sensitivity toprecursor concentrations. Measurements made with this system at Sacramento,California, between April–December 2020 revealed that theatmospheric chemical regime followed a seasonal cycle. O3 formation wasVOC-limited (NOx-rich) during the early spring, transitioned toNOx-limited during the summer due to increased concentrations ofambient VOCs with high O3 formation potential, and then returned toVOC-limited (NOx-rich) during the fall season as the concentrations ofambient VOCs decreased and NOx increased. This seasonal pattern ofO3 sensitivity is consistent with the cycle of biogenic emissions inCalifornia. The direct chamber O3 sensitivity measurements matchedsemi-direct measurements of HCHO/NO2 ratios from the TROPOsphericMonitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (Sentinel-5P) satellite. Furthermore, the satellite observations showed thatthe same seasonal cycle in O3 sensitivity occurred over most of theentire state of California, with only the urban cores of the very largecities remaining VOC-limited across all seasons. The O3-nonattainmentdays (MDA8 O3>70 ppb)more »have O3 sensitivity in theNOx-limited regime, suggesting that a NOx emissions controlstrategy would be most effective at reducing these peak O3concentrations. In contrast, a large portion of the days with MDA8 O3concentrations below 55 ppb were in the VOC-limited regime, suggesting thatan emissions control strategy focusing on NOx reduction would increaseO3 concentrations. This challenging situation suggests that emissionscontrol programs that focus on NOx reductions will immediately lowerpeak O3 concentrations but slightly increase intermediate O3concentrations until NOx levels fall far enough to re-enter theNOx-limited regime. The spatial pattern of increasing and decreasingO3 concentrations in response to a NOx emissions control strategyshould be carefully mapped in order to fully understand the public healthimplications.« less
  3. The effect of vapor-wall deposition on secondary organic aerosol (SOA) formation has gained significant attention; however, uncertainties in experimentally derived SOA mass yields due to uncertainties in particle-wall deposition remain. Different approaches have been used to correct for particle-wall deposition in SOA formation studies, each having its own set of assumptions in determining the particle-wall loss rate. In volatile and intermediate-volatility organic compound (VOC and IVOC) systems in which SOA formation is governed by kinetically limited growth, the effect of vapor-wall deposition on SOA mass yields can be constrained by using high surface area concentrations of seed aerosol to promote the condensation of SOA-forming vapors onto seed aerosol instead of the chamber walls. However, under such high seed aerosol levels, the presence of significant coagulation may complicate the particle-wall deposition correction. Here, we present a model framework that accounts for coagulation in chamber studies in which high seed aerosol surface area concentrations are used. For the α-pinene ozonolysis system, we find that after accounting for coagulation, SOA mass yields remain approximately constant when high seed aerosol surface area concentrations ( ≥  8000 µm2 cm−3) are used, consistent with our prior study (Nah et al., 2016) showing that α-pinene ozonolysis SOA formation is governed bymore »quasi-equilibrium growth. In addition, we systematically assess the uncertainties in the calculated SOA mass concentrations and yields between four different particle-wall loss correction methods over the series of α-pinene ozonolysis experiments. At low seed aerosol surface area concentrations (< 3000 µm2 cm−3), the SOA mass yields at peak SOA growth obtained from the particle-wall loss correction methods agree within 14 %. However, at high seed aerosol surface area concentrations ( ≥  8000 µm2 cm−3), the SOA mass yields at peak SOA growth obtained from different particle-wall loss correction methods can differ by as much as 58 %. These differences arise from assumptions made in the particle-wall loss correction regarding the first-order particle-wall loss rate. This study highlights the importance of accounting for particle-wall deposition accurately during SOA formation chamber experiments and assessing the uncertainties associated with the application of the particle-wall deposition correction method when comparing and using SOA mass yields measured in different studies.« less